Test: check requirements, lower timesteps

app.py

@@ -105,7 +105,7 @@ def generate_images(selected_class, num_images, progress=gr.Progress()):
     x = torch.randn(num_images, 1, 28, 28).to(device)
     y = torch.tensor([class_idx] * num_images).to(device)
     
-    for t in progress.tqdm(noise_scheduler.timesteps, desc="Generating image", total=noise_scheduler.config.num_train_timesteps): # 
+    for t in progress.tqdm(range(2), desc="Generating image", total=noise_scheduler.config.num_train_timesteps): # 
         with torch.no_grad():
             residual = model_classcond_native(x, t, y)
         x = noise_scheduler.step(residual, t, x).prev_sample

requirements.txt

@@ -4,5 +4,4 @@ diffusers==0.29.2
 safetensors==0.4.3
 huggingface_hub==0.23.4
 accelerate==0.32.1
-numpy==1.26.4
-json==2.0.9
+numpy==1.26.4